Abstract
The metabolome is composed of a vast number of small-molecule metabolites that exhibit a diversity of physical and chemical properties and exist over a wide dynamic range in biological samples. Multiple analytical techniques, used in a complementary manner, are required to achieve high coverage of the metabolome. MS is playing a central role in metabolomics research. Herein, we present a brief overview of the MS-based technologies employed for high-throughput metabolomics. These technologies range from chromatography–MS techniques, such as GC–MS and LC–MS, to chromatography-free techniques, such as direct infusion, matrix-assisted and matrix-free laser desorption/ionization, imaging and some new ambient ionization approaches. Chemoinformatics and bioinformatics tools are widely available to facilitate successful metabolomics studies by turning the complex metabolomics data into biological information through streamlined data processing, analysis and interpretation.
Papers of special note have been highlighted as: ▪ of interest ▪▪ of considerable interest
Bibliography
- 1 Fiehn O. Metabolomics – the link between genotypes and phenotypes. Plant Mol. Biol.48(1–2),155–171 (2002).▪ Definition of metabolomics and clarification of the difference between targeted metabolite analysis, metabolic profiling and metabolic fingerprinting.Crossref, Medline, CAS, Google Scholar
- 2 Goodacre R, Vaidyanathan S, Dunn WB, Harrigan GG, Kell DB. Metabolomics by numbers: acquiring and understanding global metabolite data. Trends Biotechnol.22(5),245–252 (2004).Crossref, Medline, CAS, Google Scholar
- 3 Nicholson JK, Lindon JC, Holmes E. ‘Metabonomics’: understanding the metabolic responses of living systems to pathophysiological stimuli via multivariate statistical analysis of biological NMR spectroscopic data. Xenobiotica29(11),1181–1189 (1999).▪ A technical definition of metabonomics.Crossref, Medline, CAS, Google Scholar
- 4 Raamsdonk LM, Teusink B, Broadhurst D et al. A functional genomics strategy that uses metabolome data to reveal the phenotype of silent mutations. Nat. Biotechnol.19(1),45–50 (2001).Crossref, Medline, CAS, Google Scholar
- 5 ter Kuile BH, Westerhoff HV. Transcriptome meets metabolome: hierarchical and metabolic regulation of the glycolytic pathway. FEBS Lett.500(3),169–171 (2001).Crossref, Medline, CAS, Google Scholar
- 6 Kim K, Aronov P, Zakharkin SO et al. Urine metabolomics analysis for kidney cancer detection and biomarker discovery. Mol. Cell Proteomics8(3),558–570 (2009).Crossref, Medline, CAS, Google Scholar
- 7 Sreekumar A, Poisson LM, Rajendiran TM et al. Metabolomic profiles delineate potential role for sarcosine in prostate cancer progression. Nature457(7231),910–914 (2009).▪▪ A milestone in cancer metabolomics that identified sarcosine as a potential small-molecule biomarker for prostate cancer progression.Crossref, Medline, CAS, Google Scholar
- 8 Wikoff WR, Anfora AT, Liu J et al. Metabolomics analysis reveals large effects of gut microflora on mammalian blood metabolites. Proc. Natl Acad. Sci. USA106(10),3698–3703 (2009).Crossref, Medline, CAS, Google Scholar
- 9 Scherling C, Ulrich K, Ewald D, Weckwerth W. A metabolic signature of the beneficial interaction of the endophyte Paenibacillus sp. isolate and in vitro-grown poplar plants revealed by metabolomics. Mol. Plant Microbe Interact.22(8),1032–1037 (2009).Crossref, Medline, CAS, Google Scholar
- 10 Bottcher C, von Roepenack-Lahaye E, Schmidt J et al. Metabolome analysis of biosynthetic mutants reveals a diversity of metabolic changes and allows identification of a large number of new compounds in Arabidopsis. Plant Physiol.147(4),2107–2120 (2008).Crossref, Medline, Google Scholar
- 11 MacKenzie DA, Defernez M, Dunn WB et al. Relatedness of medically important strains of Saccharomyces cerevisiae as revealed by phylogenetics and metabolomics. Yeast25(7),501–512 (2008).Crossref, Medline, CAS, Google Scholar
- 12 Viant MR. Recent developments in environmental metabolomics. Mol. Biosyst.4(10),980–986 (2008).Crossref, Medline, CAS, Google Scholar
- 13 Duarte NC, Becker SA, Jamshidi N et al. Global reconstruction of the human metabolic network based on genomic and bibliomic data. Proc. Natl Acad. Sci. USA104(6),1777–1782 (2007).Crossref, Medline, CAS, Google Scholar
- 14 Fiehn O. Combining genomics, metabolome analysis, and biochemical modelling to understand metabolic networks. Comp. Funct. Genomics2(3),155–168 (2001).Crossref, Medline, CAS, Google Scholar
- 15 Dunn WB, Bailey NJ, Johnson HE. Measuring the metabolome: current analytical technologies. Analyst130(5),606–625 (2005).Crossref, Medline, CAS, Google Scholar
- 16 Weckwerth W, Fiehn O. Can we discover novel pathways using metabolomic analysis? Curr. Opin. Biotechnol.13(2),156–160 (2002).Crossref, Medline, CAS, Google Scholar
- 17 Villas-Boas SG, Mas S, Akesson M, Smedsgaard J, Nielsen J. Mass spectrometry in metabolome analysis. Mass Spectrom. Rev.24(5),613–646 (2005).Crossref, Medline, CAS, Google Scholar
- 18 Villas-Boas SG, Hojer-Pedersen J, Akesson M, Smedsgaard J, Nielsen J. Global metabolite analysis of yeast: evaluation of sample preparation methods. Yeast22(14),1155–1169 (2005).Crossref, Medline, CAS, Google Scholar
- 19 Dunn WB, Ellis DI. Metabolomics: current analytical platforms and methodologies. Trends Anal. Chem.24(4),285–294 (2005).Crossref, CAS, Google Scholar
- 20 Fiehn O, Kopka J, Dormann P, Altmann T, Trethewey RN, Willmitzer L. Metabolite profiling for plant functional genomics. Nat. Biotechnol.18(11),1157–1161 (2000).Crossref, Medline, CAS, Google Scholar
- 21 Dettmer K, Aronov PA, Hammock BD. Mass spectrometry-based metabolomics. Mass Spectrom. Rev.26(1),51–78 (2007).▪ A good review on mass spectrometry-related metabolomics.Crossref, Medline, CAS, Google Scholar
- 22 Issaq HJ, Van QN, Waybright TJ, Muschik GM, Veenstra TD. Analytical and statistical approaches to metabolomics research. J. Sep. Sci.32(13),2183–2199 (2009).Crossref, Medline, CAS, Google Scholar
- 23 Fiehn O. Extending the breadth of metabolite profiling by gas chromatography coupled to mass spectrometry. Trends Analyt. Chem.27(3),261–269 (2008).Crossref, Medline, CAS, Google Scholar
- 24 Pasikanti KK, Ho PC, Chan EC. Gas chromatography/mass spectrometry in metabolic profiling of biological fluids. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci.871(2),202–211 (2008).Crossref, Medline, CAS, Google Scholar
- 25 Metz TO, Zhang Q, Page JS et al. The future of liquid chromatography-mass spectrometry (LC–MS) in metabolic profiling and metabolomic studies for biomarker discovery. Biomark. Med.1(1),159–185 (2007).Crossref, Medline, CAS, Google Scholar
- 26 Lu W, Bennett BD, Rabinowitz JD. Analytical strategies for LC–MS-based targeted metabolomics. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci.871(2),236–242 (2008).Crossref, Medline, CAS, Google Scholar
- 27 Cubbon S, Antonio C, Wilson J, Thomas-Oates J. Metabolomic applications of HILIC–LC–MS. Mass Spectrom. Rev. DOI: 10.1002/mas.20252 (2009) (Epub ahead of print).Google Scholar
- 28 Leon C, Rodriguez-Meizoso I, Lucio M et al. Metabolomics of transgenic maize combining Fourier transform-ion cyclotron resonance–mass spectrometry, capillary electrophoresis–mass spectrometry and pressurized liquid extraction. J. Chromatogr. A1216(43),7314–7323 (2009).Crossref, Medline, CAS, Google Scholar
- 29 Chalcraft KR, Lee R, Mills C, Britz-McKibbin P. Virtual quantification of metabolites by capillary electrophoresis–electrospray ionization–mass spectrometry: predicting ionization efficiency without chemical standards. Anal. Chem.81(7),2506–2515 (2009).Crossref, Medline, CAS, Google Scholar
- 30 Lee R, Ptolemy AS, Niewczas L, Britz-McKibbin P. Integrative metabolomics for characterizing unknown low-abundance metabolites by capillary electrophoresis–mass spectrometry with computer simulations. Anal. Chem.79(2),403–415 (2007).Crossref, Medline, CAS, Google Scholar
- 31 Ramautar R, Demirci A, de Jong GJ. Capillary electrophoresis in metabolomics. Trends Anal. Chem.25(5),455–466 (2006).Crossref, CAS, Google Scholar
- 32 Kuhara T. Gas chromatographic–mass spectrometric urinary metabolome analysis to study mutations of inborn errors of metabolism. Mass Spectrom. Rev.24(6),814–827 (2005).Crossref, Medline, CAS, Google Scholar
- 33 Qualley AV, Dudareva N. Metabolomics of plant volatiles. Methods Mol. Biol.553,329–343 (2009).Crossref, Medline, CAS, Google Scholar
- 34 Halket JM, Waterman D, Przyborowska AM, Patel RK, Fraser PD, Bramley PM. Chemical derivatization and mass spectral libraries in metabolic profiling by GC/MS and LC/MS/MS. J. Exp. Bot.56(410),219–243 (2005).Crossref, Medline, CAS, Google Scholar
- 35 Birkemeyer C, Kolasa A, Kopka J. Comprehensive chemical derivatization for gas chromatography–mass spectrometry-based multi-targeted profiling of the major phytohormones. J. Chromatogr. A.993(1–2),89–102 (2003).Crossref, Medline, CAS, Google Scholar
- 36 Maurer HH. Role of gas chromatography–mass spectrometry with negative ion chemical ionization in clinical and forensic toxicology, doping control, and biomonitoring. Ther. Drug Monit.24(2),247–254 (2002).Crossref, Medline, CAS, Google Scholar
- 37 Liebeke M, Wunder A, Lalk M. A rapid microwave-assisted derivatization of bacterial metabolome samples for gas chromatography/mass spectrometry analysis. Anal. Biochem. DOI: 10.1016/j.ab.2009.04.030 (2009) (Epub ahead of print).Medline, Google Scholar
- 38 Mastovska K, Lehotay SJ. Practical approaches to fast gas chromatography-mass spectrometry. J. Chromatogr. A.1000(1–2),153–180 (2003).Crossref, Medline, CAS, Google Scholar
- 39 Kawana S, Nakagawa K, Hasegawa Y, Kobayashi H, Yamaguchi S. Improvement of sample throughput using fast gas chromatography mass-spectrometry for biochemical diagnosis of organic acid disorders. Clin. Chim. Acta392(1–2),34–40 (2008).Crossref, Medline, CAS, Google Scholar
- 40 Libardoni M, Fiehn O, Hawkins J, King TM. Analysis of complex metabolomics samples using high throughput GC TOF and GC×GC TOFMS: the importance of deconvolution and GC×GC. Asian J. Pharmacodynamics Pharmacokinetics7(3),201–209 (2007).Google Scholar
- 41 Zrostlikova J, Hajslova J, Cajka T. Evaluation of two-dimensional gas chromatography–time-of-flight mass spectrometry for the determination of multiple pesticide residues in fruit. J. Chromatogr. A.1019(1–2),173–186 (2003).Crossref, Medline, CAS, Google Scholar
- 42 Li X, Xu Z, Lu X et al. Comprehensive two-dimensional gas chromatography/time-of-flight mass spectrometry for metabonomics: biomarker discovery for diabetes mellitus. Anal. Chim. Acta633(2),257–262 (2009).Crossref, Medline, CAS, Google Scholar
- 43 Ralston-Hooper K, Hopf A, Oh C, Zhang X, Adamec J, Sepulveda MS. Development of GC×GC/TOF–MS metabolomics for use in ecotoxicological studies with invertebrates. Aquat. Toxicol.88(1),48–52 (2008).Crossref, Medline, CAS, Google Scholar
- 44 Mohler RE, Dombek KM, Hoggard JC, Pierce KM, Young ET, Synovec RE. Comprehensive analysis of yeast metabolite GC × GC-TOFMS data: combining discovery-mode and deconvolution chemometric software. Analyst132(8),756–767 (2007).Crossref, Medline, CAS, Google Scholar
- 45 Koek MM, Muilwijk B, van Stee LL, Hankemeier T. Higher mass loadability in comprehensive two-dimensional gas chromatography–mass spectrometry for improved analytical performance in metabolomics analysis. J. Chromatogr. A1186(1–2),420–429 (2008).Crossref, Medline, CAS, Google Scholar
- 46 Fiehn O, Robertson D, Griffin J et al. The metabolomics standards initiative (MSI). Metabolomics3,175–178 (2007).Crossref, CAS, Google Scholar
- 47 Bunk B, Kucklick M, Jonas R et al. MetaQuant: a tool for the automatic quantification of GC/MS-based metabolome data. Bioinformatics22(23),2962–2965 (2006).Crossref, Medline, CAS, Google Scholar
- 48 Borner J, Buchinger S, Schomburg D. A high-throughput method for microbial metabolome analysis using gas chromatography/mass spectrometry. Anal. Biochem.367(2),143–151 (2007).Crossref, Medline, Google Scholar
- 49 Halket JM, Przyborowska A, Stein SE, Mallard WG, Down S, Chalmers RA. Deconvolution gas chromatography/mass spectrometry of urinary organic acids – potential for pattern recognition and automated identification of metabolic disorders. Rapid Commun. Mass Spectrom.13(4),279–284 (1999).Crossref, Medline, CAS, Google Scholar
- 50 Stein SE. An integrated method for spectrum extraction and compound identification from gas chromatography/mass spectrometry data. J. Am. Soc. Mass Spec.10(8),770–781 (1999).Crossref, CAS, Google Scholar
- 51 Baran R, Kochi H, Saito N et al. MathDAMP: a package for differential analysis of metabolite profiles. BMC Bioinformatics7,530 (2006).Crossref, Medline, Google Scholar
- 52 Smith CA, Want EJ, O’Maille G, Abagyan R, Siuzdak G. XCMS: processing mass spectrometry data for metabolite profiling using nonlinear peak alignment, matching, and identification. Anal. Chem.78(3),779–787 (2006).Crossref, Medline, CAS, Google Scholar
- 53 Benton HP, Wong DM, Trauger SA, Siuzdak G. XCMS2: processing tandem mass spectrometry data for metabolite identification and structural characterization. Anal. Chem.80(16),6382–6389 (2008).Crossref, Medline, CAS, Google Scholar
- 54 Katajamaa M, Oresic M. Processing methods for differential analysis of LC–MS profile data. BMC Bioinformatics6,179 (2005).Crossref, Medline, Google Scholar
- 55 Katajamaa M, Miettinen J, Oresic M. MZmine: toolbox for processing and visualization of mass spectrometry based molecular profile data. Bioinformatics22(5),634–636 (2006).Crossref, Medline, CAS, Google Scholar
- 56 Lommen A. MetAlign: interface-driven, versatile metabolomics tool for hyphenated full-scan mass spectrometry data preprocessing. Anal. Chem.81(8),3079–3086 (2009).Crossref, Medline, CAS, Google Scholar
- 57 De Vos RC, Moco S, Lommen A, Keurentjes JJ, Bino RJ, Hall RD. Untargeted large-scale plant metabolomics using liquid chromatography coupled to mass spectrometry. Nat. Protoc.2(4),778–791 (2007).Crossref, Medline, CAS, Google Scholar
- 58 Luedemann A, Strassburg K, Erban A, Kopka J. TagFinder for the quantitative analysis of gas chromatography–mass spectrometry (GC–MS)-based metabolite profiling experiments. Bioinformatics24(5),732–737 (2008).Crossref, Medline, CAS, Google Scholar
- 59 Broeckling CD, Reddy IR, Duran AL, Zhao X, Sumner LW. MET-IDEA: data extraction tool for mass spectrometry-based metabolomics. Anal. Chem.78(13),4334–4341 (2006).Crossref, Medline, CAS, Google Scholar
- 60 Hiller K, Hangebrauk J, Jager C, Spura J, Schreiber K, Schomburg D. MetaboliteDetector: comprehensive analysis tool for targeted and nontargeted GC/MS based metabolome analysis. Anal. Chem.81(9),3429–3439 (2009).Crossref, Medline, CAS, Google Scholar
- 61 LECO. ChromaTOF software. LECO Inc., 1150 Blanchard St., Bellefonte, PA, USA 16823–8618 (2009).Google Scholar
- 62 Plumb R, Castro-Perez J, Granger J, Beattie I, Joncour K, Wright A. Ultra-performance liquid chromatography coupled to quadrupole-orthogonal time-of-flight mass spectrometry. Rapid Commun. Mass Spectrom.18(19),2331–2337 (2004).▪ Introduction of ultrahigh-performance LC for LC–MS.Crossref, Medline, CAS, Google Scholar
- 63 Wilson ID, Plumb R, Granger J, Major H, Williams R, Lenz EM. HPLC-MS-based methods for the study of metabonomics. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci.817(1),67–76 (2005).Crossref, Medline, CAS, Google Scholar
- 64 Nordstrom A, Want E, Northen T, Lehtio J, Siuzdak G. Multiple ionization mass spectrometry strategy used to reveal the complexity of metabolomics. Anal. Chem.80(2),421–429 (2008).Crossref, Medline, Google Scholar
- 65 Robb DB, Covey TR, Bruins AP. Atmospheric pressure photoionization: an ionization method for liquid chromatography–mass spectrometry. Anal. Chem.72(15),3653–3659 (2000).Crossref, Medline, CAS, Google Scholar
- 66 Marchi I, Rudaz S, Veuthey JL. Atmospheric pressure photoionization for coupling liquid-chromatography to mass spectrometry: a review. Talanta78(1),1–18 (2009).Crossref, Medline, CAS, Google Scholar
- 67 Morris HR, Paxton T, Dell A et al. High sensitivity collisionally-activated decomposition tandem mass spectrometry on a novel quadrupole/orthogonal-acceleration time-of-flight mass spectrometer. Rapid Commun. Mass Spectrom.10(8),889–896 (1996).Crossref, Medline, CAS, Google Scholar
- 68 Hu Q, Noll RJ, Li H, Makarov A, Hardman M, Graham Cooks R. The Orbitrap: a new mass spectrometer. J. Mass Spectrom.40(4),430–443 (2005).Crossref, Medline, CAS, Google Scholar
- 69 Marshall AG, Hendrickson CL, Jackson GS. Fourier transform ion cyclotron resonance mass spectrometry: a primer. Mass Spectrom. Rev.17(1),1–35 (1998).Crossref, Medline, CAS, Google Scholar
- 70 Yates JR, Cociorva D, Liao L, Zabrouskov V. Performance of a linear ion trap-Orbitrap hybrid for peptide analysis. Anal. Chem.78(2),493–500 (2006).Crossref, Medline, CAS, Google Scholar
- 71 Dunn WB, Broadhurst D, Brown M et al. Metabolic profiling of serum using ultra performance liquid chromatography and the LTQ-Orbitrap mass spectrometry system. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci.871(2),288–298 (2008).Crossref, Medline, CAS, Google Scholar
- 72 Dunn WB. Current trends and future requirements for the mass spectrometric investigation of microbial, mammalian and plant metabolomes. Phys. Biol.5(1),11001 (2008).Crossref, Medline, Google Scholar
- 73 t’Kindt R, Alaerts G, Vander Heyden Y, Deforce D, Van Bocxlaer J. Broad-spectrum separations in metabolomics using enhanced polar LC stationary phases: a dedicated evaluation using plant metabolites. J. Sep. Sci.30(13),2002–2011 (2007).Crossref, Medline, Google Scholar
- 74 Bell DS, Jones AD. Solute attributes and molecular interactions contributing to “U-shape” retention on a fluorinated high-performance liquid chromatography stationary phase. J. Chromatogr. A1073(1–2),99–109 (2005).Crossref, Medline, CAS, Google Scholar
- 75 Yoshida H, Yamazaki J, Ozawa S, Mizukoshi T, Miyano H. Advantage of LC–MS metabolomics methodology targeting hydrophilic compounds in the studies of fermented food samples. J. Agric. Food Chem.57(4),1119–1126 (2009).Crossref, Medline, CAS, Google Scholar
- 76 Alpert AJ. Hydrophilic-interaction chromatography for the separation of peptides, nucleic acids and other polar compounds. J. Chromatogr.499,177–196 (1990).Crossref, Medline, CAS, Google Scholar
- 77 Tolstikov VV, Fiehn O. Analysis of highly polar compounds of plant origin: combination of hydrophilic interaction chromatography and electrospray ion trap mass spectrometry. Anal. Biochem.301(2),298–307 (2002).Crossref, Medline, CAS, Google Scholar
- 78 Kamleh A, Barrett MP, Wildridge D, Burchmore RJ, Scheltema RA, Watson DG. Metabolomic profiling using Orbitrap Fourier transform mass spectrometry with hydrophilic interaction chromatography: a method with wide applicability to analysis of biomolecules. Rapid Commun. Mass Spectrom.22(12),1912–1918 (2008).Crossref, Medline, CAS, Google Scholar
- 79 Pesek JJ, Matyska MT, Fischer SM, Sana TR. Analysis of hydrophilic metabolites by high-performance liquid chromatography–mass spectrometry using a silica hydride-based stationary phase. J. Chromatogr. A1204(1),48–55 (2008).Crossref, Medline, CAS, Google Scholar
- 80 Callahan DL, Souza DD, Bacic A, Roessner U. Profiling of polar metabolites in biological extracts using diamond hydride-based aqueous normal phase chromatography. J. Sep. Sci.32(13),2273–2280 (2009).Crossref, Medline, CAS, Google Scholar
- 81 Pesek JJ, Matyska MT, Loo JA, Fischer SM, Sana TR. Analysis of hydrophilic metabolites in physiological fluids by HPLC–MS using a silica hydride-based stationary phase. J. Sep. Sci.32(13),2200–2208 (2009).Crossref, Medline, CAS, Google Scholar
- 82 Weisenberg SA, Butterfield TR, Fischer SM, Rhee KY. Suitability of silica hydride stationary phase, aqueous normal phase chromatography for untargeted metabolomic profiling of Enterococcus faecium and Staphylococcus aureus. J. Sep. Sci.32(13),2262–2265 (2009).Crossref, Medline, CAS, Google Scholar
- 83 SIELC Technologies. 65E Palatine Road, Suite 221, Prospect Heights, IL 60070, USA (2009).Google Scholar
- 84 Myint KT, Aoshima K, Tanaka S, Nakamura T, Oda Y. Quantitative profiling of polar cationic metabolites in human cerebrospinal fluid by reversed-phase nanoliquid chromatography/mass spectrometry. Anal. Chem.81(3),1121–1129 (2009).Crossref, Medline, CAS, Google Scholar
- 85 Ceglarek U, Leichtle A, Brugel M et al. Challenges and developments in tandem mass spectrometry based clinical metabolomics. Mol. Cell Endocrinol.301(1–2),266–271 (2009).Crossref, Medline, CAS, Google Scholar
- 86 Sawada Y, Akiyama K, Sakata A et al. Widely targeted metabolomics based on large-scale MS/MS data for elucidating metabolite accumulation patterns in plants. Plant Cell Physiol.50(1),37–47 (2009).Crossref, Medline, CAS, Google Scholar
- 87 Hager JW, Le Blanc JC. High-performance liquid chromatography-tandem mass spectrometry with a new quadrupole/linear ion trap instrument. J. Chromatogr. A.1020(1),3–9 (2003).Crossref, Medline, CAS, Google Scholar
- 88 Hager JW, Yves Le Blanc JC. Product ion scanning using a Q-q-Q linear ion trap (Q TRAP) mass spectrometer. Rapid Commun. Mass Spectrom.17(10),1056–1064 (2003).Crossref, Medline, CAS, Google Scholar
- 89 Kitteringham NR, Jenkins RE, Lane CS, Elliott VL, Park BK. Multiple reaction monitoring for quantitative biomarker analysis in proteomics and metabolomics. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci.877(13),1229–1239 (2009).▪ Good review on LC–MS data processing approaches.Crossref, Medline, CAS, Google Scholar
- 90 Katajamaa M, Oresic M. Data processing for mass spectrometry-based metabolomics. J. Chromatogr. A.1158(1–2),318–328 (2007).Crossref, Medline, CAS, Google Scholar
- 91 Tautenhahn R, Bottcher C, Neumann S. Highly sensitive feature detection for high resolution LC/MS. BMC Bioinformatics9,504 (2008).Crossref, Medline, Google Scholar
- 92 Lange E, Tautenhahn R, Neumann S, Gropl C. Critical assessment of alignment procedures for LC–MS proteomics and metabolomics measurements. BMC Bioinformatics9,375 (2008).Crossref, Google Scholar
- 93 Peters S, van Velzen E, Janssen HG. Parameter selection for peak alignment in chromatographic sample profiling: objective quality indicators and use of control samples. Anal. BioAnal. Chem.394(5),1273–1281 (2009).Crossref, Medline, CAS, Google Scholar
- 94 Sysi-Aho M, Katajamaa M, Yetukuri L, Oresic M. Normalization method for metabolomics data using optimal selection of multiple internal standards. BMC Bioinformatics8,93 (2007).Crossref, Medline, Google Scholar
- 95 Scholz M, Fiehn O. SetupX – a public study design database for metabolomic projects. Pac. Symp. Biocomput.2007,169–180 (2007).▪ Detailed introduction of the Human Metabolome Database (HMDB).Crossref, Google Scholar
- 96 Wishart DS, Tzur D, Knox C et al. HMDB: the Human Metabolome Database. Nucleic Acids Res.35,D521–D526 (2007).Crossref, Medline, CAS, Google Scholar
- 97 Knox C, Shrivastava S, Stothard P, Eisner R, Wishart DS. BioSpider: a web server for automating metabolome annotations. Pac. Symp. Biocomput.2007,145–156 (2007).Crossref, Google Scholar
- 98 Koulman A, Cao M, Faville M, Lane G, Mace W, Rasmussen S. Semi-quantitative and structural metabolic phenotyping by direct infusion ion trap mass spectrometry and its application in genetical metabolomics. Rapid Commun. Mass Spectrom.23(15),2253–2263 (2009).Crossref, Medline, CAS, Google Scholar
- 99 Ohta D, Shibata D, Kanaya S. Metabolic profiling using Fourier-transform ion-cyclotron-resonance mass spectrometry. Anal. BioAnal. Chem.389(5),1469–1475 (2007).Crossref, Medline, CAS, Google Scholar
- 100 Nakamura Y, Kimura A, Saga H et al. Differential metabolomics unraveling light/dark regulation of metabolic activities in Arabidopsis cell culture. Planta227(1),57–66 (2007).Crossref, Medline, CAS, Google Scholar
- 101 Oikawa A, Nakamura Y, Ogura T et al. Clarification of pathway-specific inhibition by Fourier transform ion cyclotron resonance/mass spectrometry-based metabolic phenotyping studies. Plant Physiol.142(2),398–413 (2006).Crossref, Medline, CAS, Google Scholar
- 102 Han J, Danell RM, Patel JR et al. Towards high-throughput metabolomics using ultrahigh-field Fourier transform ion cyclotron resonance mass spectrometry. Metabolomics4(2),128–140 (2008).Crossref, Medline, CAS, Google Scholar
- 103 Takahashi H, Kai K, Shinbo Y et al. Metabolomics approach for determining growth-specific metabolites based on Fourier transform ion cyclotron resonance mass spectrometry. Anal. BioAnal. Chem.391(8),2769–2782 (2008).▪ Application of the mass spectral stitching technique for metabolic fingerprinting by infusion–FTMS.Crossref, Medline, CAS, Google Scholar
- 104 Southam AD, Payne TG, Cooper HJ, Arvanitis TN, Viant MR. Dynamic range and mass accuracy of wide-scan direct infusion nanoelectrospray fourier transform ion cyclotron resonance mass spectrometry-based metabolomics increased by the spectral stitching method. Anal. Chem.79(12),4595–4602 (2007).Crossref, Medline, CAS, Google Scholar
- 105 Staack RF, Varesio E, Hopfgartner G. The combination of liquid chromatography/tandem mass spectrometry and chip-based infusion for improved screening and characterization of drug metabolites. Rapid Commun. Mass Spectrom.19(5),618–626 (2005).Crossref, Medline, CAS, Google Scholar
- 106 Taylor NS, Weber RJM, Southam AD et al. A new approach to toxicity testing in Daphniamagna: application of high throughput FT-ICR mass spectrometry metabolomics. Metabolomics5(1),44–58 (2009).Crossref, CAS, Google Scholar
- 107 Karas M, Hillenkamp F. Laser desorption ionization of proteins with molecular masses exceeding 10,000 daltons. Anal. Chem.60(20),2299–2301 (1988).Crossref, Medline, CAS, Google Scholar
- 108 Vaidyanathan S, Gaskell S, Goodacre R. Matrix-suppressed laser desorption/ionisation mass spectrometry and its suitability for metabolome analyses. Rapid Commun. Mass Spectrom.20(8),1192–1198 (2006).Crossref, Medline, CAS, Google Scholar
- 109 Wang JN, Zhou Y, Zhu TY, Wang X, Guo YL. Prediction of acute cellular renal allograft rejection by urinary metabolomics using MALDI–FTMS. J. Proteome Res.7(8),3597–3601 (2008).Crossref, Medline, CAS, Google Scholar
- 110 Fraser PD, Enfissi EM, Goodfellow M, Eguchi T, Bramley PM. Metabolite profiling of plant carotenoids using the matrix-assisted laser desorption ionization time-of-flight mass spectrometry. Plant J.49(3),552–564 (2007).Crossref, Medline, CAS, Google Scholar
- 111 Sun G, Yang K, Zhao Z, Guan S, Han X, Gross RW. Shotgun metabolomics approach for the analysis of negatively charged water-soluble cellular metabolites from mouse heart tissue. Anal. Chem.79(17),6629–6640 (2007).Crossref, Medline, CAS, Google Scholar
- 112 Guo Z, He L. A binary matrix for background suppression in MALDI–MS of small molecules. Anal. BioAnal. Chem.387(5),1939–1944 (2007).Crossref, Medline, CAS, Google Scholar
- 113 Shroff R, Rulisek L, Doubsky J, Svatos A. Acid-base-driven matrix-assisted mass spectrometry for targeted metabolomics. Proc. Natl Acad. Sci. USA106(25),10092–10096 (2009).▪ Good review on the matrix-free LDI–MS techniques.Crossref, Medline, Google Scholar
- 114 Peterson DS. Matrix-free methods for laser desorption/ionization mass spectrometry. Mass Spectrom. Rev.26(1),19–34 (2007).▪ Development of desorption/ionization on silicon for matrix-free laser desorption/ionization MS.Crossref, Medline, CAS, Google Scholar
- 115 Wei J, Buriak JM, Siuzdak G. Desorption-ionization mass spectrometry on porous silicon. Nature399(6733),243–246 (1999).Crossref, Medline, CAS, Google Scholar
- 116 Woo HK, Northen TR, Yanes O, Siuzdak G. Nanostructure-initiator mass spectrometry: a protocol for preparing and applying NIMS surfaces for high-sensitivity mass analysis. Nat. Protoc.3(8),1341–1349 (2008).Crossref, Medline, CAS, Google Scholar
- 117 Northen TR, Yanes O, Northen MT et al. Clathrate nanostructures for mass spectrometry. Nature449(7165),1033–1036 (2007).Crossref, Medline, CAS, Google Scholar
- 118 Amantonico AF, Glaus R, Zenobi R. Negative mode nanostructure-initiator mass spectrometry for detection of phosphorylated metabolites. Metabolomics DOI: 10.1007/s11306-009-0163-5 (2009) (Epub advance of print).▪ One of the pioneering publications on tissue imaging by MALDI–MS.Google Scholar
- 119 Caprioli RM, Farmer TB, Gile J. Molecular imaging of biological samples: localization of peptides and proteins using MALDI-TOF MS. Anal. Chem.69(23),4751–4760 (1997).Crossref, Medline, CAS, Google Scholar
- 120 Cha S, Song Z, Nikolau BJ, Yeung ES. Direct profiling and imaging of epicuticular waxes on Arabidopsis thaliana by laser desorption/ionization mass spectrometry using silver colloid as a matrix. Anal. Chem.81(8),2991–3000 (2009).Crossref, Medline, CAS, Google Scholar
- 121 Cha S, Yeung ES. Colloidal graphite-assisted laser desorption/ionization mass spectrometry and MSn of small molecules. 1. Imaging of cerebrosides directly from rat brain tissue. Anal. Chem.79(6),2373–2385 (2007).Crossref, Medline, CAS, Google Scholar
- 122 Zhang H, Cha S, Yeung ES. Colloidal graphite-assisted laser desorption/ionization MS and MS(n) of small molecules. 2. Direct profiling and MS imaging of small metabolites from fruits. Anal. Chem.79(17),6575–6584 (2007).Crossref, Medline, CAS, Google Scholar
- 123 Cha S, Zhang H, Ilarslan HI et al. Direct profiling and imaging of plant metabolites in intact tissues by using colloidal graphite-assisted laser desorption ionization mass spectrometry. Plant J.55(2),348–360 (2008).Crossref, Medline, CAS, Google Scholar
- 124 Li Y, Shrestha B, Vertes A. Atmospheric pressure molecular imaging by infrared MALDI mass spectrometry. Anal. Chem.79(2),523–532 (2007).Crossref, Medline, CAS, Google Scholar
- 125 Li Y, Shrestha B, Vertes A. Atmospheric pressure infrared MALDI imaging mass spectrometry for plant metabolomics. Anal. Chem.80(2),407–420 (2008).▪ Development of the desorption ESI–MS technique.Crossref, Medline, CAS, Google Scholar
- 126 Takats Z, Wiseman JM, Gologan B, Cooks RG. Mass spectrometry sampling under ambient conditions with desorption electrospray ionization. Science306(5695),471–473 (2004).Crossref, Medline, CAS, Google Scholar
- 127 Cooks RG, Ouyang Z, Takats Z, Wiseman JM. Detection technologies. Ambient mass spectrometry. Science311(5767),1566–1570 (2006).Crossref, Medline, CAS, Google Scholar
- 128 Jackson AU, Werner SR, Talaty N et al. Targeted metabolomic analysis of Escherichia coli by desorption electrospray ionization and extractive electrospray ionization mass spectrometry. Anal. Biochem.375(2),272–281 (2008).Crossref, Medline, CAS, Google Scholar
- 129 Dill AL, Ifa DR, Manicke NE, Ouyang Z, Cooks RG. Mass spectrometric imaging of lipids using desorption electrospray ionization. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. (2008).Medline, Google Scholar
- 130 Wiseman JM, Ifa DR, Song Q, Cooks RG. Tissue imaging at atmospheric pressure using desorption electrospray ionization (DESI) mass spectrometry. Angew Chem. Int. Ed. Engl.45(43),7188–7192 (2006).Crossref, Medline, CAS, Google Scholar
- 131 Chen H, Venter A, Cooks RG. Extractive electrospray ionization for direct analysis of undiluted urine, milk and other complex mixtures without sample preparation. Chem. Commun. (Camb.) (19),2042–2044 (2006).Crossref, Medline, Google Scholar
- 132 Gu H, Chen H, Pan Z et al. Monitoring diet effects via biofluids and their implications for metabolomics studies. Anal. Chem.79(1),89–97 (2007).▪ Development of the direct analysis in real-time ionization technique.Crossref, Medline, CAS, Google Scholar
- 133 Cody RB, Laramee JA, Durst HD. Versatile new ion source for the analysis of materials in open air under ambient conditions. Anal. Chem.77(8),2297–2302 (2005).Crossref, Medline, CAS, Google Scholar
- 134 Zhao Y, Lam M, Wu D, Mak R. Quantification of small molecules in plasma with direct analysis in real time tandem mass spectrometry, without sample preparation and liquid chromatographic separation. Rapid Commun. Mass Spectrom.22(20),3217–3224 (2008).Crossref, Medline, CAS, Google Scholar
- 135 Yu S, Crawford E, Tice J, Musselman B, Wu JT. Bioanalysis without sample cleanup or chromatography: the evaluation and initial implementation of direct analysis in real time ionization mass spectrometry for the quantification of drugs in biological matrixes. Anal. Chem.81(1),193–202 (2009).Crossref, Medline, CAS, Google Scholar
- 136 Nemes P, Vertes A. Laser ablation electrospray ionization for atmospheric pressure, in vivo, and imaging mass spectrometry. Anal. Chem.79(21),8098–8106 (2007).Crossref, Medline, CAS, Google Scholar
- 137 Nemes P, Barton AA, Li Y, Vertes A. Ambient molecular imaging and depth profiling of live tissue by infrared laser ablation electrospray ionization mass spectrometry. Anal. Chem.80(12),4575–4582 (2008).Crossref, Medline, CAS, Google Scholar
- 138 Nemes P, Barton AA, Vertes A. Three-dimensional imaging of metabolites in tissues under ambient conditions by laser ablation electrospray ionization mass spectrometry. Anal. Chem.81(16),6668–6675 (2009).Crossref, Medline, CAS, Google Scholar
- 139 Sripadi P, Nazarian J, Hathout Y, Hoffman EP, Vertes A. In vitro analysis of metabolites from the untreated tissue of Torpedo californica electric organ by mid-infrared laser ablation electrospray ionization mass spectrometry. Metabolomics5,263–276 (2009).Crossref, CAS, Google Scholar
- 140 Wold S, Esbensen K, Geladi P. Principal component analysis. Chemometrics Intel. Lab. Syst.2,37–52 (1987).Crossref, CAS, Google Scholar
- 141 Wold S, Ruhe A, Wold H, Dunn WI. The collinearity problem in linear regression. The partial least squares approach to generalized inverses. SIAM J. Sci. Comput.5,735–743 (1984).Crossref, Google Scholar
- 142 Li X, Lu X, Tian J, Gao P, Kong H, Xu G. Application of fuzzy c-means clustering in data analysis of metabolomics. Anal. Chem.81(11),4468–4475 (2009).Crossref, Medline, CAS, Google Scholar
- 143 Trygg J, Wold S. Orthogonal projections to latent structures (O-PLS). J. Chemometrics119(16),119–128 (2002).Crossref, Google Scholar
- 144 Wiklund S, Johansson E, Sjostrom L et al. Visualization of GC/TOF–MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. Anal. Chem.80(1),115–122 (2008).Crossref, Medline, CAS, Google Scholar
- 145 van den Berg RA, Hoefsloot HC, Westerhuis JA, Smilde AK, van der Werf MJ. Centering, scaling, and transformations: improving the biological information content of metabolomics data. BMC Genomics7,142 (2006).▪▪ Good paper on how to reliably annotate metabolites from accurate masses, elemental compositions and istopic distribution patterns.Crossref, Medline, Google Scholar
- 146 Kind T, Fiehn O. Metabolomic database annotations via query of elemental compositions: mass accuracy is insufficient even at less than 1 ppm. BMC Bioinformatics7,234 (2006).▪ An example for the identification of a novel endogenous metabolite through chemical synthesis and LC–MS/MS.Crossref, Medline, Google Scholar
- 147 Kalisiak J, Trauger SA, Kalisiak E et al. Identification of a new endogenous metabolite and the characterization of its protein interactions through an immobilization approach. J. Am. Chem. Soc.131(1),378–386 (2009).Crossref, Medline, CAS, Google Scholar
- 148 Wang Y, Xiao J, Suzek TO, Zhang J, Wang J, Bryant SH. PubChem: a public information system for analyzing bioactivities of small molecules. Nucleic Acids Res.37,W623–W633 (2009).▪ Another publication on introduction of the HMDB.Crossref, Medline, CAS, Google Scholar
- 149 Wishart DS, Knox C, Guo AC et al. HMDB: a knowledgebase for the human metabolome. Nucleic Acids Res.37,D603–D610 (2009).Crossref, Medline, CAS, Google Scholar
- 150 Wishart DS, Knox C, Guo AC et al. DrugBank: a knowledgebase for drugs, drug actions and drug targets. Nucleic Acids Res.36,D901–D906 (2008).Crossref, Medline, CAS, Google Scholar
- 151 Wishart DS, Knox C, Guo AC et al. DrugBank: a comprehensive resource for in silico drug discovery and exploration. Nucleic Acids Res.34,D668–D672 (2006).Crossref, Medline, CAS, Google Scholar
- 152 Fahy E, Sud M, Cotter D, Subramaniam S. LIPID MAPS online tools for lipid research. Nucleic Acids Res.35,W606–W612 (2007).Crossref, Medline, Google Scholar
- 153 Sud M, Fahy E, Cotter D et al. LMSD: LIPID MAPS structure database. Nucleic Acids Res.35,D527–D532 (2007).Crossref, Medline, CAS, Google Scholar
- 154 Brown M, Dunn WB, Dobson P et al. Mass spectrometry tools and metabolite-specific databases for molecular identification in metabolomics. Analyst134(7),1322–1332 (2009).Crossref, Medline, CAS, Google Scholar
- 155 Kopka J, Schauer N, Krueger S et al. GMD@CSB.DB: the Golm Metabolome Database. Bioinformatics21(8),1635–1638 (2005).Crossref, Medline, CAS, Google Scholar
- 156 Smith CA, O’Maille G, Want EJ et al. METLIN: a metabolite mass spectral database. Ther. Drug Monit.27(6),747–751 (2005).Crossref, Medline, CAS, Google Scholar
- 157 Matsuda F, Yonekura-Sakakibara K, Niida R, Kuromori T, Shinozaki K, Saito K. MS/MS spectral tag-based annotation of non-targeted profile of plant secondary metabolites. Plant J.57(3),555–577 (2009).Crossref, Medline, CAS, Google Scholar
- 158 Cui Q, Lewis IA, Hegeman AD et al. Metabolite identification via the Madison Metabolomics Consortium Database. Nat. Biotechnol.26(2),162–164 (2008).Crossref, Medline, CAS, Google Scholar
- 159 Kanehisa M, Goto S, Hattori M et al. From genomics to chemical genomics: new developments in KEGG. Nucleic Acids Res.34,D354–D357 (2006).Crossref, Medline, CAS, Google Scholar
- 160 Karp PD, Ouzounis CA, Moore-Kochlacs C et al. Expansion of the BioCyc collection of pathway/genome databases to 160 genomes. Nucleic Acids Res.33(19),6083–6089 (2005).Crossref, Medline, CAS, Google Scholar
- 161 Krummenacker M, Paley S, Mueller L, Yan T, Karp PD. Querying and computing with BioCyc databases. Bioinformatics21(16),3454–3455 (2005).Crossref, Medline, CAS, Google Scholar
- 162 Caspi R, Foerster H, Fulcher CA et al. MetaCyc: a multiorganism database of metabolic pathways and enzymes. Nucleic Acids Res.34,D511–D516 (2006).Crossref, Medline, CAS, Google Scholar
- 163 Krieger CJ, Zhang P, Mueller LA et al. MetaCyc: a multiorganism database of metabolic pathways and enzymes. Nucleic Acids Res.32,D438–D442 (2004).Crossref, Medline, CAS, Google Scholar
- 164 Karp PD, Riley M, Paley SM, Pellegrini-Toole A. The MetaCyc Database. Nucleic Acids Res.30(1),59–61 (2002).Crossref, Medline, CAS, Google Scholar
- 165 Romero P, Wagg J, Green ML, Kaiser D, Krummenacker M, Karp PD. Computational prediction of human metabolic pathways from the complete human genome. Genome Biol.6(1),R2 (2005).Crossref, Medline, Google Scholar
- 166 Matthews L, Gopinath G, Gillespie M et al. Reactome knowledgebase of human biological pathways and processes. Nucleic Acids Res.37,D619–D622 (2009).Crossref, Medline, CAS, Google Scholar
- 167 Vastrik I, D’Eustachio P, Schmidt E et al. Correction: reactome: a knowledge base of biologic pathways and processes. Genome Biol.10(2),402 (2009).Crossref, Medline, Google Scholar
- 168 Vastrik I, D’Eustachio P, Schmidt E et al. Reactome: a knowledge base of biologic pathways and processes. Genome Biol.8(3),R39 (2007).Crossref, Medline, Google Scholar
- 201 PubChem – compound- and species-specific database http://pubchem.ncbi.nlm.nih.gov/Google Scholar
- 202 HMDB – compound- and species-specific database www.hmdb.ca/Google Scholar
- 203 Lipid Maps – compound- and species-specific database www.lipidmaps.org/data/databases.htmlGoogle Scholar
- 204 KNApSAcK – compound- and species-specific database http://kanaya.naist.jp/KNApSAcK/Google Scholar
- 205 MMD – compound- and species-specific database http://dbkgroup.org/MMDGoogle Scholar
- 206 NIST08 – reference spectral library/database www.nist.gov/srd/nist1.htmGoogle Scholar
- 207 GMD – reference spectral library/database http://csbdb.mpimp-golm.mpg.de/csbdb/gmd/gmd.htmlGoogle Scholar
- 208 METLIN – reference spectral library/database http://metlin.scripps.edu/Google Scholar
- 209 MassBank – reference spectral library/database www.massbank.jp/Google Scholar
- 210 MS2T – reference spectral library/database http://prime.psc.riken.jp/lcms/ms2tview/ms2tview.htmlGoogle Scholar
- 211 MMCD – reference spectral library/database http://mmcd.nmrfam.wisc.edu/Google Scholar
- 212 KEGG – pathway-specific database www.genome.jp/kegg/Google Scholar
- 213 BioCyc – pathway-specific database http://biocyc.org/Google Scholar
- 214 EcoCyc – pathway-specific database http://biocyc.org/ecocyc/index.shtmlGoogle Scholar
- 215 MetaCyc – pathway-specific database http://biocyc.org/metacyc/index.shtmlGoogle Scholar
- 216 HumanCyc – pathway-specific database http://humancyc.org/Google Scholar
- 217 Reactome – pathway-specific database http://reactome.org/Google Scholar

